JP6080184B1 - Data collection method used to classify cancer life - Google Patents

Abstract

[Object] To detect not only early cancer in a specific organ, but also to determine a high risk group for micro cancer at any site and early cancer in clinical cancer stage, classify the stage of advanced cancer, and Contribute to prevention and treatment. A serum is applied to a support immersed in a buffer solution, the support is electrophoresed at a predetermined liquid temperature and fractionated, and proteins in the serum are separated to obtain an ALP isozyme staining solution. ALP isozyme is detected by color development, and the protein image and ALP isozyme are combined, and the mobility, chromosome shape, shading, etc. are determined to find the movement of the minute cancer that occurs, tumor marker In addition to the analysis results of the above, the risk of the tumor and the risk of cancer are evaluated to classify the life of the cancer, the decrease in albumin fraction, the α1-globulin fraction, the α2-globulin fraction appearing in the protein image The risk of tumor and the risk assessment of cancer are classified into 3 to 4 stages by determining the change state of the increase in the fraction and the γ-globulin fraction. [Selection] Figure 2

Description

The present invention relates to a method for collecting data used in detecting blood and urine of a person suspected of cancer, biochemically detecting a minute cancer, and quantitatively detecting and evaluating cancer at an early stage. In particular, the present invention relates to a data collection method for use in detecting both micro cancers in the preclinical cancer stage and clinical cancer stage in the life of cancer, and classifying the life of cancer by accurately analyzing the risk.

  It is important for cancer treatment to detect and diagnose cancer at an early stage. In particular, there are cases where small cancers that were discovered early were completely cured with natural healing power. Therefore, many methods for finding cancers such as stomach cancer, lung cancer, colon cancer, liver cancer, breast cancer and the like at an early stage have been proposed and implemented.

In addition, cancerous cells repeatedly divide to form cancerous tissue and appear as diseases. As shown in FIG. 1, the life of a cancer is classified into three stages of “pre-cancerous stage (healthy stage)”, “preclinical cancer stage”, and “clinical cancer stage”. Although canceration of cells occurs in the precancerous stage, it is difficult to visually confirm the presence of cancer at this point because the population of cancer cells is very small until the preclinical cancer stage. The cancer that can be usually detected with the naked eye is a cancer with a diameter of 10 mm or more in the clinical cancer stage, and consists of about 1 billion (10 ⁹ ) or more cancer cells. It is this cancer of the clinical cancer stage that is generally recognized as a disease and is the subject of treatment.

  Cancer cells often create special components that are not found in normal cells. In addition, a very small amount of a component may be produced in a normal person and a large amount in a cancer patient. Such components characteristic of cancer cells are referred to as “tumor markers” in the sense of cancer cell markers.

  Such tumor markers are produced only in cancer cells and fetuses such as “alpha-fetoprotein, α-fetoprotein, AFP” in liver cancer, and “carcinoembryonic antigen, CEA” in gastric cancer and colorectal cancer. Protein, tumor-specific antigen such as pancreatic cancer that reacts with “sugar chain antigen 19-9, carbohydrate antigen 19-9, CA19-9”, “gonadotropin, human chorionic gonadotropin, human chorionic gonadotropin, HCG in uterine choriocarcinoma” ”, Hormones such as“ calcitonin or calcitonin, calcitonin ”in parathyroid cancer, and cancerous“ alkaline phosphatase (hereinafter referred to as “ALP”) in bone cancer and liver cancer.

  This ALP is an important tumor marker under correct conditions. It is an enzyme that has the function of separating phosphate. In humans, ALP has several different molecular weights for each organ such as placenta and small intestine in addition to the bone and liver. There is. When there are a plurality of types of enzymes having the same action for each organ, such as ALP, they are called isozymes. For example, in patients with bone cancer, liver cancer, multiple myeloma, etc., an isozyme having a molecular weight different from that of a normal human enzyme is produced. In these cancer cells, the functions of the genes that control the respective isozymes have lost their normality, and thus the isozymes have different pattern changes. Therefore, if such an isozyme pattern is examined and accurately evaluated, it is possible to discover a minute cancer that has occurred in bone, liver, large intestine, lung, or the like.

  Therefore, conventionally, a method for examining ALP isozymes by electrophoresis is proposed. In this test method, serum proteins are separated by electrophoresis, reacted with a naphthol phosphate compound, and a liberated naphthol substance is diazotized with a diazonium salt to develop a color, thereby detecting an isozyme.

This ALP isozyme test method is performed, for example, by the following means.
(1) Application of sample First, cellulogel that has been immersed in a buffer for electrophoresis for 1 hour or longer is cut into 2.5 × 6 cm pieces, and 1 cm from the cathode side, from human blood to be evaluated for cancer. Apply 8-10 μl of separated serum. In the case of high activity, the coating amount is adjusted.
(2) Electrophoresis Electrophoresis is performed at 100 V until albumin moves 1 cm from the anode end. It is desirable to cool at this time.
(3) After completion of staining electrophoresis After completion of staining electrophoresis, the cellulogel is further cut in half, and protein staining is performed with one piece and ALP staining is performed with the other piece. In ALP staining, a membrane that has been migrated on a filter paper soaked with a staining solution is layered so as not to allow air to enter, and is shielded from light and heated at 37 ° C. for about 1 hour. Fix in 1% acetic acid after staining.

(4) Evaluation method A protein image and an ALP isozyme are combined, and the mobility, chromosome shape, shading, etc. of each isozyme are observed. A band from I to VI is detected in the serum by electrophoresis, but when differentiated from the antigenic point, liver ALP, placental ALP, small intestine ALP, systemic ALP, and bone ALP of different organs are derived. It was thought to be due to the difference between these five types of modified isozymes and sugar chains.

Normal human serum ALP is mainly hepatic (α ₂ position) and often has α ₂ > α ₂ β. Intestinal properties are frequently detected in the secretory types of blood groups O and B. In childhood, osseous (stained as a broad active zone) appears, but heat-resistant placental ALP appears in late pregnancy. Liver ALP rising in biliary disease is of the main alpha _2-position derived from hepatic, intrahepatic, extrahepatic cholestasis, metastatic liver cancer, the drug-induced disorders such as a polymeric alpha _1-position of the Isozymes appear. In chronic hepatitis and cirrhosis, the appearance frequency of small intestinal ALP is high. Bone ALP increases in Kur disease, Paget's disease, hyperparathyroidism, hyperthyroidism, fracture, bone metastasis of cancer, osteosarcoma, etc. ALP may be seen. Abnormalities of ALP detected by electrophoresis include those caused by tumor production, binding to immunoglobulins, modification by sialic acid and neuraminitase.

(5) Tumor-producing ALP isozymes include placental-type Regan ALP and Nagao ALP, and small intestine-type Kasahara ALP as tumor-producing ALP detected by the above-described evaluation method. Placental ALP is detected as a sharp band. Placental ALP is frequently detected in ovarian cancer and uterine cancer, and is detected at a frequency of 10 to 15% in cancer patients. Kasahara ALP of the small intestine is migrated to the position of ALP1 by cellulose acetate membrane electrophoresis, but can be evaluated by changing the mobility of ALP1 to the cathode side by Triton X-100 treatment, and 5% polyacrylamide gel electrophoresis Then, it can be confirmed from the fact that it migrates to the most anode side. Moreover, there exists the characteristic inhibited by L-phenylalanine. Kasahara ALP is detected in about 15% of cancer patients.

  As shown in Table 4, several types of ALP isozymes such as hepatic, osseous, placental, and small intestine appear in human serum for normal and various diseases, among which electrophoretic mobility, There are considerable differences in heat resistance, degree of inhibition by various amino acids, immunoreactivity, etc., and they are used separately.

ALP is a dimer having a molecular weight of 120,000 to 160,000, and exists as a complex bound to the cell membrane of each tissue cell. However, a large (high) molecular ALP that has become a fragment of the cell membrane at the time of tissue injury is blood. May play inside. Low molecular weight ALP derived from hepatic, osseous, placental, and small intestine is α1 by general electrophoresis. While moving between the ～Beta, different mobility on the type of polymeric ALP a support (in particular the presence or absence of molecular sieve effect), cellulose acetate film, the agar alpha _1-position components remain (liver-derived) origin Although it is divided (the latter is peeled off at the time of dyeing and is not detected), in polyacrylamide gel and starch gel, the mobility is reduced by the molecular sieve effect, and it is divided into the origin position and the two fractions that move slightly thereafter.

  The hepatocarcinogenic ALP described later is detected as a component having a higher mobility than hepatic in the polyacrylamide gel, but is not detected in the cellulose acetate film and agar as hepatic. Also, immunoglobulin-binding ALP is better separated from small intestine by polyacrylamide gel. Therefore, a cellulose acetate membrane or agar and polyacrylamide gel are used in combination for analysis of serum ALP isozyme by electrophoresis.

  Various techniques related to a system for predicting a cancer onset risk that changes based on a result of cancer screening under specific conditions have been proposed. For example, as disclosed in Japanese Patent Laid-Open No. 2006-302222 “Cancer Risk Prediction System and Method, and Cancer Derivative Method” of Patent Document 1, at least computing means and storage means are provided, and clinical cancer onset occurs under specific conditions. A prediction system for predicting risk, wherein the storage means stores past screening results in a specific high-accuracy cancer screening capable of detecting preclinical cancer based on specific numerical values indicating the presence of cancer. A high-accuracy cancer screening clustering database that is classified into a healthy state, an apparently healthy state in which the possibility of the presence of the cancer cannot be denied, and a clinical cancer state, and the data can be referred to for each classification. In the high-accuracy cancer screening clustering database, re-examination results of the high-accuracy cancer screening received after a specific period for each classification can be referred to for each classification. A high-accuracy cancer screening reexamination result database, and calculating a correlation between the high-accuracy cancer screening clustering data and the high-accuracy cancer screening reexamination result data, A clinical cancer state distribution calculating means for calculating a clinical cancer state distribution with a specific period as a variable, and a specific patient who has undergone the high-accuracy cancer screening is calculated based on the result of the medical examination. A prediction system is proposed that includes a simulation means for generating a prediction of the likelihood of being affected.

JP 2006-302222 A

  However, the ALP isozyme testing method described above is difficult to detect unless the cancer has grown to a certain size. Therefore, in the conventional methods for detecting and evaluating cancer using isozymes, the prevalence of correct diagnosis (sensitivity) and the prevalence of non-pathological diagnosis (specificity) are low. This prevalence rate is the rate at which cancer patients are correctly evaluated as having cancer, and the non-morbidity rate is the rate at which healthy individuals are correctly evaluated as not having cancer. Therefore, conventional methods for detecting cancer by isozymes are mainly performed as a kind of auxiliary test for diagnosing cancer or as a follow-up test for treating cancer. .

The inventor of the present invention biochemically detects microcancer by using the pattern change per fixed time of ALP isozyme, ΔCEA (carcinoembryonic antigen) and Δferritin as an indicator of the presence of microcancer ( We focused on the method (including induction of tumor markers). ALP plays an important role in the process of canceration, which is regarded as a dedifferentiation or heterodifferentiation phenomenon. There is a close relationship between cancer cell growth and ALP I to ALP IV isozyme patterns, with total ALP activity in the serum within the normal range. Therefore, by analyzing the change (Δ) in the tumor marker value and isozyme over a certain period of time, it is possible to estimate a minute cancer having 10 ⁴ to 10 ⁹ cells (10 μg to 1 g in weight). That is, a new early cancer evaluation method was invented by analyzing pattern changes of ALP isozymes.
Such tumor markers include “alpha-fetoprotein, α-fetoprotein, AFP” in liver cancer, proteins produced in cancer cells such as “carcinoembryonic antigen, CEA” in gastric cancer and colon cancer, “ Tumor-specific antigens such as pancreatic cancer that react with carbohydrate antigen 19-9, carbohydrate antigen 19-9, CA19-9, “gonadotropin, human chorionic gonadotropin, HCG” in uterine choriocarcinoma, deputy There are various types such as hormones such as “calcitonin or calcitonin, calcitonin” in thyroid cancer, and cancerous “alkaline phosphatase (hereinafter referred to as“ ALP ”) in bone cancer and liver cancer.

FIG. 16 is a graph showing the positive rate of each tumor marker in early colorectal cancer, benign colorectal disease, and healthy individuals. FIG. 17 is a graph showing the positive rate of each tumor marker in early colorectal cancer, benign colorectal disease, and healthy individuals.
By using a single tumor marker, it is possible to discover a minute cancer that has occurred in bone, liver, intestine, lung, or the like. However, as many oncologists have pointed out, if the sensitivity of the prevalence rate (sensitivity) is improved, the specificity, that is, the non-morbidity rate (specificity) decreases, so the degree of accuracy ( improvement in accuracy) could not be expected. Thus, as shown in Table 5, the inventors of the present invention have dealt with a plurality of tumor markers having relatively low specificities and have found effective composite markers. For example, attention was paid to CEA × TPA, FT / Fe, and combinations thereof. This table was investigated for early colorectal cancer and lung cancer. With CEA and TPA single tumor markers, it is impossible to increase both sensitivity and specificity, but we focused on the fact that increasing the combination of composite markers can improve the accuracy of sensitivity and accuracy.

  As shown in FIG. 17, it is possible to distinguish early cancer and benign tumor (benign disease) in early colorectal cancer, benign colorectal disease and healthy individuals. This is because the inventor of the present invention has found a composite marker that distinguishes benign tumors (benign diseases) and healthy individuals (normal) as shown in the graph showing the positive rate of each tumor marker in FIG. . Therefore, classification is possible by using a composite marker (Fe / SA) that distinguishes between a healthy person (normal) and cancer in the first stage and a distinction between cancer and benign tumor (benign disease) in the second stage. become. In order to avoid the causal involvement of this inflammatory disease, the C reactive protein value (C inflammatory protein value, CRP value) and the sialic acid value were measured together when evaluating the α1-globulin fraction. We focused on the fact that it can be distinguished by subtracting the contributing part of inflammation.

Furthermore, the inventor of the present invention focused on using cancer screening (differential diagnosis) for analysis of serum protein fractions for cancers with 10 ⁹ or more cells. This diagnostic method for screening for cancer using serum protein fractions is inexpensive and simple, and is easy for clinicians to use. We considered that the cancer life in the “preclinical cancer stage” can be classified by combining the tumor markers, and the cancer in the “clinical cancer stage” can be classified by adding serum protein fraction analysis and using them together.

The present invention has been developed to solve such problems. That is, the object of the present invention is to comprehensively evaluate by examining whether there is a microcancer somewhere in the body, and analyzing the ALP isozyme pattern and tumor marker, or serum protein fraction. In addition to discovering early cancers in specific organs, we identify high-risk groups of micro-cancers at any site and early cancers in clinical cancer stages, and classify advanced cancer stages to prevent cancer. The purpose is to provide a method for classifying the life of a cancer that contributes to treatment and can correctly evaluate the course of treatment and suggest scientific treatment for cancer patients.
In other words, by judging the distinction between normal and cancer in the first stage and judging the distinction between cancer and benign tumor in the second stage, the pre-clinical stage cancer and the stage of clinical cancer stage in the life of the cancer It is an object of the present invention to provide a data collection method for use in classifying the life of a cancer that can be detected, accurately determined, and classified.

In order to detect the movement of a minute cancer that occurs in the human body and analyze the data of the tumor risk and the cancer risk in two stages of preclinical cancer stage and clinical cancer stage , A data collection method used to classify a lifetime,
About data used for preclinical cancer stage analysis,
In the ALP I to ALP IV pattern of the ALP isozyme, data on the appearance and ratio of ALP I, activity values of ALP II and ALP III were collected, examination of the numerical data ratio, and steepness of ALP II and ALP III Analyzing data on the proliferation activity of cancer cells from APA determined from the ALP isozyme angle indicating
Furthermore, in order to avoid the cause of inflammatory diseases, it also occurs in inflammatory diseases from numerical data obtained by combining C reactive protein values (C inflammatory protein values, CRP values) and sialic acid values. by analyzing by subtracting the numerical data of the involved parts, and data analysis for the presence of micro-cancer and its growth conditions occurring,
About data used for analysis of clinical cancer stage,
A decrease in albumin fraction appearing in the protein image,
Collect data of change states of α1-globulin fraction, α2-globulin fraction and γ-globulin fraction increase, and analyze each data
Furthermore, in order to avoid the cause of inflammatory diseases, the data of the C reactive protein value (C inflammatory protein value, CRP value) and the sialic acid value data are combined in the data analysis of the protein image. In order to analyze the risk of cancer and the risk assessment of cancer in several stages by subtracting the numerical data of the involved part that also occurs in inflammatory diseases from the measured numerical data and analyzing it,
Serum is applied to a support immersed in a buffer solution, the support is electrophoresed at a predetermined liquid temperature, fractionated, proteins in the serum are separated, and developed with an ALP isozyme staining solution. The ALP isozyme is detected, and the protein image and the ALP isozyme are combined to collect each data relating to the mobility, chromosome shape, and shading of each isozyme .

Further, the present invention is to detect the movement of a minute cancer that occurs in the human body and to analyze the data by dividing the risk of the tumor and the risk of cancer into two stages of preclinical cancer stage and clinical cancer stage. A data collection method used to classify cancer life,
About data used for preclinical cancer stage analysis,
In the ALP I to ALP IV pattern of the ALP isozyme, data on the appearance and ratio of ALP I, activity values of ALP II and ALP III were collected, examination of the numerical data ratio, and steepness of ALP II and ALP III Analyzing data on the proliferation activity of cancer cells from APA determined from the ALP isozyme angle indicating
Furthermore, in order to avoid the cause of inflammatory diseases, it also occurs in inflammatory diseases from numerical data obtained by combining C reactive protein values (C inflammatory protein values, CRP values) and sialic acid values. by analyzing by subtracting the numerical data of the involved parts, and data analysis for the presence of micro-cancer and its growth conditions occurring,
About data used for analysis of clinical cancer stage,
About cancer that became more than 1 gram in clinical cancer stage,
In the first period, when the albumin fraction is 65% or more, the α1-globulin fraction is less than 2.5%, and the γ-globulin fraction is less than 16%,
In the second period, when the albumin fraction is 60% to less than 65%, the α1-globulin fraction is 2.5% to less than 3.0%, and the γ-globulin fraction is less than 16% to less than 20%,
In the third stage, when the albumin fraction is 55% to less than 60%, the α1-globulin fraction is 3.0% to less than 4.0%, and the γ-globulin fraction is 20% to less than 23%,
The fourth stage is classified so that the risk of cancer becomes 4 levels when the albumin fraction is less than 55%, the α1-globulin fraction is 4.0% or more, and the γ-globulin fraction is 23% or more. While analyzing data,
In order to avoid the cause of inflammatory diseases, each numerical value obtained by measuring C reactive protein value (C inflammatory protein value, CRP value) and sialic acid value at the time of data analysis of the protein image In order to analyze the risk of cancer and the risk assessment of cancer in several stages by subtracting the numerical data of the part involved in inflammatory diseases from the data and analyzing it ,
Serum is applied to a support immersed in a buffer solution, the support is electrophoresed at a predetermined liquid temperature, fractionated, proteins in the serum are separated, and developed with an ALP isozyme staining solution. The ALP isozyme is detected, and the protein image and the ALP isozyme are combined to collect each data relating to the mobility, chromosome shape, and shading of each isozyme .

For use in the analysis of preclinical cancer stage, regarding the APA data obtained from the ALP isozyme,
The angle of the line connecting the anode side tangent of ALP II and the peaks of ALP II and ALP III is θ ₁ °,
From this two tangent intersection, the distance to the peak of the ALP III as Omega1cm, shown in APA = ω1 / θ _1, when the ALP IV have appeared, the intersection and ALP III - IV of the tangent of the ALP II The length to the peak can be expressed as APA = ω2 / θ ₂ with ω2 cm.

Regarding the data used for the analysis of preclinical cancer stage, the serum was heat-treated at 56 ° C. for 10 minutes to analyze the reconstructed pattern data of each ALP isozyme pattern from ALP I to ALP IV. ALP II, ALP III and ALP IV can be accurately identified.

Furthermore, the data used in the analysis of preclinical cancer stage, the proliferation activity of cancer cells from the change in the pattern of the ALP isozymes as well as data analysis,
Tumor growth level by tumor marker, stage I, ideal state without micro cancer, stage II, pre-cancer state at microgram level, stage III, pre-cancer state at milligram level, stage IV, pre-clinical cancer state, and then data analysis the state of 1g or more cancer is estimated to be present with the tumor growth of stage 5 stage of the stage V,
By using this data analysis of the change of the tumor marker over time, it is possible to analyze the data on the presence of a minute cancer and its growth state.

For data to be used for analysis of clinical cancer stage, the C reactive protein value (C inflammatory protein levels, CRP values) and the measured value of, from the numerical data of the measurement values of the sialic acid level, even in inflammatory diseases Analyzes are made by subtracting the α1-globulin fraction of the part involved .

By determining by subtracting the part that occurs also in inflammatory diseases from the α1-globulin fraction according to the high measured value of the sialic acid value, the inflammatory disease is not the cause in the evaluation, but cancer to decide.

In the data collection method used for classifying the preclinical cancer stage of the present invention, since there is a close relationship between the proliferation of cancer cells and APA, an ALP isozyme pattern is analyzed using each of these collected data. Thus, a microcancer having 10 ⁴ to 10 ⁹ cells can be detected. This ALP I often appears and it can be found that ALP I increases as the cancer progresses. ALP II is called systemic ALP and is also involved in ALP in all organs. ALP III is known to increase due to osteogenesis , cirrhosis, and chronic renal failure when ALP total activity is increased. When ALP is within the normal range, ALP III increases when there is cell neogenesis, for example, in the case of microcancer growth, liver regeneration, and slow-growing clinical cancer.

Furthermore, in the data collection method used for classifying the preclinical cancer stage of the present invention, when the progression of cancer is accelerated in clinical cancer, ALP III moves to ALP II and ALP III decreases due to neuraminidase in the blood. come. The ALP III is not high potential is a modified enzyme with dephosphorylation effects associated with growth of neoplastic cells.

The data collection method used in classifying preclinical cancer stage of the present invention, more analysis of the reconstruction patterns of the ALP each isozyme, ALP II (ALP2), ALP III (ALP3), and accurately ALP IV (ALP4) It can be identified at a high rate. In particular, although ALP IV is detected in cancer tissues at a high rate, the frequency of occurrence of ALP IV in the blood of cancer patients is said to be 1 to 30%, and its activity is low, and it is overlooked. It was mistaken for III. By analyzing the reconstruction pattern of the present invention, data capable of detecting this ALP IV at a high rate can be collected .

In the data collection method used for classifying the preclinical cancer stage of the present invention, when the identification of the ALP isozyme pattern is not clear, the stage of cancer is classified based on the tumor marker, and these stage classification models By introducing, data that can be accurately evaluated from micro cancer to clinical cancer can be collected .

As described above, by using each data collected by the data collection method of the present invention, ALP isozyme I appears when total activities such as primary liver cancer, liver invasion, congestive liver, fatty liver are increased, and ALP II is called hepatic ALP and is also found in cancerous pericardial effusion, and ALP III increases when osteogenesis, cirrhosis and chronic renal failure increase when total ALP activity is increased Since there is a close relationship between the proliferation of cancer cells and the ALP isozyme patterns of ALP I to ALP IV, analysis of these ALP isozyme patterns reveals a microcancer with 10 ⁴ to 10 ⁹ cells. And the risk of micro cancer can be evaluated.

In addition, when the identification of ALP isozyme pattern is not clear, the stage of cancer development is classified based on tumor markers, and by introducing these stage classification models, it is possible to accurately measure from minute cancer to clinical cancer. It is possible to collect data that can be evaluated easily.

In the data collection method used to classify the clinical cancer stage of the present invention, a biochemical biopsy is added to the protein fraction to accurately classify the risk after the cancer becomes 1 gram or more of clinical cancer. it can. By classifying the risk level according to the method of the present invention, it is possible to collect data that can be numerically analyzed almost accurately with respect to cancer prevention, recurrence prevention, therapeutic effects of anticancer drugs, and cancer progression.

You can clearly determine whether health foods work for you, whether you are eating well, and whether cancer treatment is appropriate. If TMCA screening is performed before and after cancer surgery, it is possible to clearly determine whether the cancer is an early stage cancer or advanced cancer without performing laparotomy. Of course, if an operation is performed and the test results of the TMCA screening are compared before and after the operation, it is possible to collect data that can easily determine whether the cancer has been left uncut or whether the operation was successful.

The data collection method used for classifying the life of the cancer of the present invention corresponds to a health barometer, and at the same time, many misdiagnosis determined by image diagnosis or the like can be surely prevented. Here, TMCA screening refers to a tumor marker comprehensive diagnosis method as described later. Data capable of comprehensive determination of toxins in the living body internal environment, that is, the degree of internal environment contamination can be collected . This is a method of collecting data used when classifying the risk comprehensively by determining the toxin produced by cancer and the so-called “tumor marker”.

  The change in protein image is a phenomenon that occurs even in chronic inflammatory diseases. It is necessary to avoid the rate of involvement due to the inflammatory disease. Therefore, it is necessary to measure the C reactive protein value (C inflammatory protein value, CRP value) and the sialic acid value together. By making this measurement, more accurate cancer classification becomes possible.

The data collection method used for classifying the life of the cancer of the present invention can be implemented for normal cancer classification. Although the criteria are slightly different for sarcomas and the like, it is possible to apply the data collection method used for classifying the life of the cancer of the present invention.

It is explanatory drawing which shows the lifetime of the cancer classified into three stages, "pre-cancer stage", "pre-clinical cancer stage", and "clinical cancer stage", and shows correlation with the size of a cancer cell. It is a flowchart which shows the judgment method in the "preclinical cancer stage" and the "clinical cancer stage" by the data collection method used when classifying the lifetime of the cancer of this invention. It is a graph which shows the pattern from ALP I of ALP isozyme in the data collection method used when classifying the preclinical cancer stage of Example 1, and ALP IV. FIG. 3 is a graph and a table showing patterns of ALP isozymes ALP I to ALP IV in the data collection method used in classifying the preclinical cancer stage of Example 1, (a) is a preoperative procedure for rectal cancer of a 60-year-old male, The postoperative ALP isozyme pattern is shown, and (b) shows the ALP isozyme of an esophageal cancer patient. FIG. 3 is a graph and a table showing patterns of ALP isozymes ALP I to ALP IV in the data collection method used in classifying the preclinical cancer stage of Example 1, wherein (a) is a breast cancer (about 1 g) of a 33 year old female. The change of the marker and isozyme before and after simple mastectomy is shown, and (b) shows the ALP isozyme before and after reoperation of the same patient. It is a graph which shows the pattern from ALP I to ALP IV in the heat processing of each isozyme in the data collection method used when classifying the preclinical cancer stage of Example 1, and a reconstitution experiment. Time course change of tumor marker in serum of stage IV gallbladder cancer patient (50 years old, female) in preclinical cancer stage classification method of Example 1 and time course of Δferritin level as an elevated type An example (b) classified into three types of invariant type and descending type is shown. FIG. 3 shows an ascending type (a) and a descending type (b) of Δferritin in the data collection method used when classifying the preclinical cancer stage of Example 1. FIG. It is explanatory drawing which shows the 5-step evaluation method by the growth process and ALP isozyme of cancer. The data collection method used in classifying clinical cancer stage of Example 2, and the protein fraction names classified, the result is a graph illustrating a unit, a reference value. The data collection method used in classifying clinical cancer stage of Example 2, a protein fraction analysis diagram classified. The data collection method used in classifying clinical cancer stage of Example 2, a distribution diagram showing the distribution of serum α1- globulin × alpha2-globulin product value in early colon cancer when classified, the upper initial Colon cancer (40 cases), middle row shows benign tumor (30 cases), and lower row shows healthy subjects (50 cases). The data collection method used in classifying clinical cancer stage of Example 2, a distribution diagram showing the distribution of serum TPA × alpha 1-globulin product value in early colon cancer when classified, the upper initial colon Cancer (40 cases), middle row shows benign tumors (30 cases), and lower row shows healthy subjects (50 cases). It is the distribution map investigated about the product value of (alpha) 1-globulin x (alpha) 2-globulin in various cancer cases. It is the distribution map investigated about the product value of TPAxalpha1-globulin in various cancer cases. It is a graph which shows the positive rate of each tumor marker in an early colon cancer, a colon benign disease, and a healthy person. It is a graph which shows the positive rate of each tumor marker in an early colon cancer, a colon benign disease, and a healthy person.

The data collection method used for classifying the life of the cancer of the present invention includes a decrease in albumin fraction, an α1-globulin fraction, an α2-globulin fraction, which appears in a protein image when classifying cancer in clinical cancer stage. It is a data collection method used when classifying the risk level of tumor and the risk level of cancer into 1 to 4 stages by identifying the change state of increase in the fraction and γ-globulin fraction.

Hereinafter, embodiments of the present invention will be described with reference to the drawings.
<Method of collecting data used to classify "micro cancers in preclinical cancer stage" in the life of cancer>
Hereinafter, a preferred embodiment of a data collection method used for classifying the lifetime of cancer of the present invention will be described with reference to the drawings.
FIG. 1 is an explanatory diagram showing the life of cancer classified into three stages of “pre-cancer stage”, “pre-clinical cancer stage”, and “clinical cancer stage”, and showing a correlation with the size of cancer cells. FIG. 2 is a flow chart showing a method of judging using data collected in “preclinical cancer stage” and “clinical cancer stage” by the data collection method used for classifying the life of the cancer of the present invention. 3 to 8 show the patterns of ALP isozyme ALP I to ALP IV in the data collection method used when classifying the preclinical cancer stage of Example 1. FIG.
The method for classifying cancer by ALP isozyme in the data collection method used for classifying the preclinical cancer stage of Example 1 of the present invention is an alkaline phosphatase (ALP) isozyme and ΔCEA that are important as indicators of differentiation related to the presence of microcancer. And Δferritin (changes per fixed time) are used to biochemically detect micro cancers (including induction of tumor markers) and classify them. ALP is widely distributed in the living body and has high ALP activity in energy metabolism, differentiation of white blood cells and mammary glands and formation of ossification, and regenerating connective tissue. Therefore, ALP is considered to play an important role in the process of canceration, which is regarded as a dedifferentiation or heterodifferentiation phenomenon. That is, in the range of ALP total activity normal serum, there is a close relationship with the isozyme pattern of proliferation and ALP I～ALP IV cancer cell, e.g., cell number 10 from pathological standpoint ⁶ The individual is presumed to be at the biological limit (reversible stage). The preclinical cancer stage classification method of Example 1 is based on the analysis of changes in tumor marker values (Δ) and isozymes over a certain period of time, and a microscopic number of 10 ⁴ to 10 ⁹ cells (10 μg to 1 g in weight). It detects cancer. Microcancer is a reversible stage, and clinical cancers of 1 g or more are considered an irreversible stage.

Detectable microcancers were classified for convenience into microgranules having a cell number of 10 ⁴ to 10 ⁶ μg and milligrams having a cell number of 10 ⁶ to 10 ⁹ mg. In the method for evaluating cancer using the ALP isozyme of the present invention, serum is applied to a support immersed in a buffer solution, the support is electrophoresed at a predetermined liquid temperature and fractionated, and proteins in the serum are separated. Separate and develop color with ALP isozyme staining solution to detect ALP isozyme, match the protein image with ALP isozyme, determine the mobility, chromosome shape, shading, etc. of each isozyme It is a method for discovering the movement of a cancer and classifying the risk of the cancer.

Classification method of cancer by our Keru ALP isozymes data acquisition method used in classifying preclinical cancer stage of Example 1, in the pattern of ALP IV from ALP I of ALP isozymes, the appearance and the ratio of the ALP I, ALP Existence of micro-cancer that develops by comprehensively analyzing the proliferative activity of cancer cells from APA calculated from the ALP isozyme angle indicating the steepness of ALP II and ALP III And the growth situation has come to be evaluated.

<Classification method>
In order to check whether there is a micro cancer somewhere in the body, ΔCEA, Δferritin, and ALP isozyme pattern are analyzed and comprehensively judged.
(1) Enzyme immunoassay (Abott) capable of quantitative determination was used for quantification of ΔCEA. Although CEA has significant individual differences, it is well known that individuals have only fluctuations within 1.0 ng / ml for a long time. Here, the amount of change between the CEA value α ₁ and the CEA value α ₂ after a certain time is represented by ΔCEA = α ₂ −α ₁ . If ΔCEA is 0.4 ± 0.1 ng / ml or more, it can be regarded as a significant fluctuation range.

(2) As Δferritin, liver-derived Δferritin was used in the embodiment of the present invention. For example, the ferritin value β ₁ and the amount of change of ferritin β ₂ after a certain time are set to Δferritin = β ₂ −β ₁ . If it is 4 ± 1 ng / ml or more, the possibility of the presence of a minute cancer is estimated. However, when there is liver parenchymal disorder, pancreatic parenchymal disorder, hemochromatosis, etc., the ferritin level rises. On the other hand, if there is iron deficiency anemia, it will go down and needs to be examined separately.

FIG. 3 is a graph showing patterns of ALP isozymes ALP I to ALP IV in the data collection method used in classifying the preclinical cancer stage of Example 1.
(3) Comprehensive determination method of ALP isozyme The ALP isozyme pattern is comprehensively determined from the following three points.
1) Appearance and proportion of ALP I.
2) Look at the ratio of the activity values of ALP II and ALP III.
3) ALP isozyme angle (AP-A) showing the steepness of ALP II and ALP III. AP-A is measured as follows (see FIG. 3). The angle of the line connecting the tangent on the anode side of ALP II and the peaks of ALP II and ALP III is defined as θ ° ₁ . From this two tangent intersections, AP-A if ω1cm the distance to the peak of the ALP III is indicated by ω1 / θ _1. If the ALPIV is considered to be emerging, if a length of up to a peak of intersection and ALP III - IV of the tangent of the ALP III and ω2cm, AP-A is calculated by ω2 / θ _2.

In addition, since the method of classifying cancer by ALP isozyme in the data collection method used when classifying the preclinical cancer stage of Example 1 is a phenomenon that occurs also in inflammatory diseases, the portion involved in the inflammatory disease is subtracted. It is necessary to judge. Therefore, more accurate cancer classification becomes possible by measuring the C reactive protein value (C inflammatory protein value, CRP value) and the sialic acid value together.

  For example, in accordance with the height of the measured value of the C reactive protein value (C inflammatory protein value, CRP value), the involved portion is subtracted from the α1-globulin fraction. Judgment is made by subtracting the degree (participation degree) of the measured value of the sialic acid value.

Next, an embodiment of a data collection method used for classifying the life of the cancer of the present invention of the present invention will be described.
FIG. 4 is a graph and a table showing patterns of ALP isozymes ALP I to ALP IV of the ALP isozyme in the preclinical cancer stage classification method of Example 1, and (a) is a preoperative and postoperative rectal cancer of a 60-year-old male. An ALP isozyme pattern is shown, and (b) shows an ALP thymogram of an esophageal cancer patient.
Case (1)
A 60-year-old male rectal cancer (stage I pmN ₀ P ₀ H ₀ ) was operated by the method of Miles. The operation day was set to zero day, and the ALP isozyme pattern before and after the operation was analyzed according to the comprehensive judgment method (FIG. 4- (a)). ALP I remains 1% on the 48th day after surgery, but disappears on the 99th day. The ALP II / III ratio shows a reversal pattern of ALP II and ALP III before the operation, and is 1.0 or less. On the other hand, ALP III decreased after the operation, and on the 48th and 99th, it was within the range of 1.8 and 1.3 and normal values (1.6 ± 0.4). AP-A also deteriorated gradually before the operation, but on the other hand, after the 48th day after the operation, it is within the range of normal values (0.1 ± 0.01 or less). After surgery, AP-A has returned to normal for a considerable number of days. This is because microscopic cancer remains around the resected rectal cancer, and it gradually shrinks. It seems to have taken time.

Case (2)
FIG. 4 (b) shows an ALP thymogram of an esophageal cancer patient (with liver metastasis). ALP total activity was within the normal range during the study period. As the number of months passes, the cancer progresses and the CEA value increases (FIG. 4- (b)). A gradual increase in ALP I, ALP II / III and AP-A was also observed.

FIG. 5 is a graph and a table showing patterns of ALP isozymes ALP I to ALP IV in the data collection method used in classifying the preclinical cancer stage of Example 1, and (a) shows breast cancer (about approx. 1g) shows changes in markers and isozymes before and after simple mastectomy, and (b) shows ALP isozymes before and after reoperation of the same patient.
Case (3)
Changes in markers and ALP isozymes before and after simple mastectomy for breast cancer (about 1 g) of a 33-year-old woman were examined (FIG. 5- (a)). The Δ values in the table are values obtained by subtracting 2 ng / ml and 1.1 ng / ml (minimum value during the period) of α-FP and CEA, respectively. ITC therapy was performed only twice after surgical resection. FIG. 4- (a) is considered to indicate a process in which one of the small cancers scattered around the surgical site gradually increases thereafter. The reaction of ALP isozyme is rapid, and α-FP and CEA appear to react with a slight delay. In particular, the peculiar pattern in which ALP III decreases can be grasped numerically well by AP-A. AP-A has been slightly decreased by the operation, but has increased rapidly over time, and is 0.294 on the 24th day after the operation, indicating a sign of recurrence.

  Next, after 9 months, the same patient recurred about 0.5 g of cancer in the vicinity of the surgical wound and resected it. Herbal medicine and basic therapy started one week before surgery. An analysis of ALP isozymes before and after reoperation is shown in FIG. The number in the figure is the number of days with the surgery date as zero. ΔCEA and Δferritin are values obtained by subtracting 1.7 ng / ml and 12 ng / ml, respectively. It is clear that ferritin and CEA increase immediately before the operation.

  Analysis of serum ALP isozymes before and after surgery in cancer patients suggests that the appearance of ALP I and the pattern changes of ALP II to III are closely related to the proliferation activity of cancer cells. It was done. It was considered possible to determine the presence and growth status of microcancer by combining the change of tumor marker over time and the analysis of ALP isozyme.

  The analysis in the preclinical cancer stage classification method of Example 1 will be described. In the present situation where identification of each isozyme of ALP II to IV is not clear, heat treatment and reconstitution experiment of each isozyme were performed in order to analyze the pattern more accurately.

<Experimental materials and methods>
FIG. 6 is a graph showing patterns of ALP I to ALP IV in the heat treatment and reconstitution experiment of each isozyme in the data collection method used when classifying the preclinical cancer stage of Example 1.
In the experiment, serum from cancer patients (FIG. 6 (a) -0) (abbreviated as serum 2) and ALP III mainly composed of ALP II and serum from 2-year-old infant (FIG. 6 (b)) are markedly reduced in ALP III. −0) (serum 3) and the pregnant woman serum (FIG. 6 (c) -0) (serum 4) immediately after birth mainly composed of ALP IV were used.

<Results of experiment>
Effects of heat treatment of each serum, FIGS. 6 (a), (b), and (c) are isozymes obtained by heat treating each serum for 10 minutes at 56 ° C. (The numbers in the figure indicate the time of heat treatment.) ALP II was fairly stable to heat at 56 ° C. for 5 minutes and had a steep peak (FIG. 6 (a)).

  ALP III is greatly inhibited by heat treatment at 56 ° C. for 10 minutes and is easily heat-resistant (FIG. 6 (b)). It was also suggested that the smooth curve of ALP III has a wide range of molecular species. ALP IV is heat-resistant, and the sharp peak shows well the characteristics derived from the late placenta (FIG. 6 (c)).

  Reconstitution experiment 1 (FIG. 6 (d)): Focusing on ALP II, sera in which serum 2 and serum 3 were combined at various ratios were electrophoresed and analyzed. Each activity of ALP II and ALP III was calculated from the total activity, and the ratio of each activity was determined. When ALP III is gradually increased to 1, 25, 75, 92%, ALP II decreases accordingly to 99, 75, 25, 8%. The peaks of ALP II and III are rounded and obtuse as the ALP III fraction increases.

  Reconstruction experiment 2 (FIG. 6 (e)) ALP I was ignored in this experiment. Serum 2 and serum 3 were mixed to obtain isozyme patterns of ALP II 30% and ALP III 70% (denoted as 0 in the figure). This is the same pattern as healthy adults. The ratio of serum 2 and 3 was kept constant, and serum 4 was gradually added for analysis. As the percentage of ALP IV (%) increased, shoulders were formed and changed to a bimodal pattern. Comparing with reconstruction experiment 1 (FIG. 6 (a)), when the ALP III peak has an acute shoulder or shows bimodality, it can be seen that the isozyme pattern has increased ALP IV. .

  Reconstitution experiment 3 (FIG. 6 (f)): In this experiment, it was examined how the isozyme pattern changes when the ratio of ALP II and ALP IV is changed. When ALP IV is 25 to 75%, the pattern of ALP II and ALP IV becomes a steep bimodal pattern with deep valleys.

  From the analysis of the reconstitution pattern of each ALP isozyme, ALP II, ALP III, and ALP IV can be easily identified. Since the molecular species in the case of cancer is diverse, the detection rate for detecting carcinoembryonic ALP is low only by checking by heat treatment. Conventionally, although ALP IV is detected in cancer tissues at a high rate, the frequency of occurrence of ALP IV in the blood of cancer patients is said to be 1 to 30%. The reason for this low detection rate is that some mechanism is involved in blood leakage of ALP IV, the possibility and the activity of ALP IV has been overlooked, and it has been mistaken for ALP III It is thought that there was considerably. By searching with reference to the isozyme pattern obtained in these reconstruction experiments, ALPIV can be detected at a higher rate. ALP I appears when the total activity of primary liver cancer, liver infiltration, congestive liver, fatty liver, etc. is increased. However, we have found that carcinoembryonic ALP I often appears even when ALP is within the normal range, and that ALP I increases as the cancer progresses (FIG. 6 (b)).

  By the way, since ALP II has been called systemic ALP, it is considered to be basic ALP. ALP III is known to increase due to osteogenesis, cirrhosis and chronic renal failure when ALP total activity is increased. When ALP is within the normal range, ALP III increases when there is cell neogenesis, for example, in the case of microcancer growth, liver regeneration, and slow-growing clinical cancer. If the progression of cancer is accelerated in clinical cancers, ALP III decreases because ALP III moves to ALP II, because neuraminitase activity in the blood works. Perhaps ALP III is likely a modified enzyme with dephosphorylation associated with neoplastic cell proliferation. Neuraminitase is an enzyme that releases sialic acid, also called sialitase, and is an asialoprotein that separates sialic acid (neuraminic acid) from oligosaccharides.

  A microcancer can be estimated by a diagnostic method using a tumor marker such as serum alkaline phosphatase (ALP) isozyme, ΔCEA, Δfetilin (difference per fixed time). However, although it is said that the appearance rate of ALP IV in serum is about 1 to 30%, ALP IV is detected at a considerable rate in cancer tissues. It is expected that even if the tumor marker is produced by cancer cells, some mechanism is mediated to get into the blood. Therefore, since it has been clarified in vitro that vitamin A and heat increase the tumor marker of cultured cancer cells, in order to confirm the presence of minute cancer, hyperthermia using far-infrared rays that has a warming effect on vitamin A and deep inside the body. An attempt was made to induce tumor markers using thermia to enhance the leakage of cancer tissue-derived markers into the blood.

<Method>
15 volunteers (4 males and 11 females) were used as subjects. These were all people who seemed healthy without cancer, and ranged in age from 28 to 38 years. As an example of clinical cancer, a stage IV gallbladder cancer patient (45 years old, female) was used. For induction, 50000 IU intramuscular injection of vitamin A (retinol palmitate) was performed, and after 1 hour, hyperthermia (56 ° C., 20 minutes) by far-infrared rays was performed on the test subject.

<Result>
FIG. 7 shows changes over time (a) in the tumor marker in the serum of stage IV gallbladder cancer patient (50 years old, female) in the data collection method used for classifying the preclinical cancer stage of Example 1, and Δ An example (b) in which the time course of the ferritin value is classified into three types of ascending type, invariant type, and descending type is shown.
Tumor marker induction was applied to patients with gallbladder cancer, and the time course of serum tumor markers was examined (FIG. 7- (a)). Ferritin and α-FP show rapid blood leakage after 6 hours. Variations of 213 ng / ml for ferritin and 50 ng / ml for α-FP were observed.

  CEA increased by only 0.3 ng / ml after 48 hours. Next, induction was applied to 15 volunteers, blood was collected before treatment and at 6, 24, 36, and 48 hours after treatment, and the difference in serum ferritin value between each time and before treatment was defined as Δferritin value. The course was classified into three types: ascending type, invariant type, and descending type (FIG. 7- (b)).

FIG. 8 shows a rising type (a) and a falling type (b) of Δferritin in the data collection method used when classifying the preclinical cancer stage of Example 1.
In the case of the invariant type (n = 4), the fluctuation range was 4 ng or less. In the rising type (n = 6), the Δ ferritin value starts to increase in 24 hours, and often reaches the maximum in 48 hours. The fluctuation range was 7 to 12 ng. In the descending type (n = 3), a rapid decrease in ferritin was observed at 6 hours (7.7 ng / ml ± 0.9 ng). The fluctuation range was 7 to 13 ng. After that, it gradually returns to the original value. Here, the ALP isozyme pattern was analyzed by our method described above. In the case of the Δferritin invariant, the activity ratio of ALP II _/ III was also in the normal value range of 1.6 ± 0.4, and AP-A was also completely normal at 0.1 or less. This invariant was an undetectable stage with a cell count of 10 ⁴ or less before the minute cancer, and it was considered that it could be regarded as a normal person. FIG. 8 (a) shows the analysis of ALP isozyme with increased Δferritin. The number in the figure is the time after the induction treatment.

  As analyzed in this chart, the ALP II / III ratio reached an abnormally low value (1.0 or less) at 36 hours and then gradually recovered. From the abnormal values of ALP II / III and AP-A by the induction method, the elevated Δferritin suggests the presence of a small cancer. Finally, the ALP isozyme analysis of the descending type is shown in FIG. 8 (b). In the case of the descending type, the ALP II / III ratio shows an abnormally low value in 6 hours, and then gradually returns to the original value. AP-A shows a value close to a normal value after the sixth hour. By analogy from the fact that it fluctuates with Δferritin in a temporal relationship, it is thought that the Δferritin descending type may indicate the presence of microcancer with inflammation.

  Thus, even if there is a slight variation, the induction method is performed on the same subject, and if ΔCEA is 0.4 ± 0.1 ng / ml or more and Δferritin value is 4 to 7 ng / ml or more, It is necessary to promote a search for microcancer. It is confirmed by performing analysis of ALP isozyme on it. In particular, the presence of a heat-resistant ALP isozyme fraction remaining after heat treatment at 56 ° C. for 10 minutes and an ultra-trace measurement method for ALP activity (65 ° C., 10 minutes heat treatment) by fluorescence spectrophotometry If used together with measuring thermostable ALP activity, the presence of microcancer is further ensured.

  In clinical cancer, ΔCEA is 1.0 ± 0.1 ng / ml or more, and Δferritin value is 20 ng / ml or more. In the present invention, only the ascending type was shown in the induction pattern of clinical cancer, but the descending type is also quite frequent. Both the ascending and descending types of volunteers are thought to reduce the induction pattern of clinical cancer. Further investigation is required to determine whether the difference in the presence of descending and ascending microcancers is only the presence or absence of inflammation, or whether the cancer is present in a different state. Of course, careful examination is necessary for inflammation of the parenchymal organs in which the ferritin level increases and hemochromatosis. The pattern analysis of LDH isozymes is also an important material. When serum iron is low, the ferritin level is low, so induction is performed after returning the serum iron level to normal. Care should be taken because ferritin levels tend to be low in cancers of the digestive system. In addition, there may be a temporary rapid increase in ferritin levels due to fasting. In the case of simple inflammation such as hepatitis, the ferritin level only decreases rapidly, and no abnormality is observed in ΔCEA or ALP isozyme.

By vitamin A and far-infrared hyperthermia, it was divided into a type in which Δferritin rises, a type in which it declines, and an invariant type. The invariant was considered a healthy person who did not have microcancer. If Δferritin was 4 to 20 ng / ml, and ΔCEA was 0.4 to 1.0 ng / ml, it was considered that the presence of microcancer could be estimated. In addition, in the analysis of ALP isozyme, the ratio of ALP I, the ratio of ALP II _/ III, and the change in AP-A (with ALP activity within the normal range) can make the presence of microcancer more deterministic. .

FIG. 9 is an explanatory diagram showing a 5-stage evaluation method using cancer growth processes and ALP isozymes.
By classifying the tumor growth level by screening for tumor markers into several stages of tumor growth, cancers that appear in apparently healthy individuals are discovered and the risk of the cancers is evaluated. For example, this tumor growth level classification includes stages with two or more abnormal levels, an ideal state without micro-cancer is stage I, pre-cancer states are stage II, III, pre-clinical cancer The stage was set to stage IV, and the stage estimated to be 1 g or more of cancer was stage V.

<Method of classifying “cancer in clinical stage” in life of cancer>
Example 2 is a method of classifying “clinical cancer stage cancer” in a data collection method used for classifying the life of a cancer. The data collection method used for classifying the life of cancer in Example 2 is a method of screening cancer by multivariate analysis of serum protein fractions. The screening by the method of Example 2 is a method that leads to an appropriate treatment method by early detection of cancer, and is performed when there is a method of definitive diagnosis by a close examination after simple screening. The present invention is not intended to finally diagnose the presence or absence of a disease or disorder, but is a method implemented as a pre-stage of a close examination for a definitive diagnosis. In the method of classifying “clinical cancer stage cancer” in Example 2, protein fractionation is described using symbols such as α, β, and γ. Some symbols are used in a different meaning from symbols such as α, β, and γ used in the method of classifying “cancer in cancer stage”.

  The method of Example 2 is a determination method in the “clinical cancer stage” shown in the flowchart of FIG. Screening of cancer with the protein fraction alone by the method of Example 2 is performed by blocking albumin [%], α1-globulin fraction [%], α2-globulin fraction [%] and γ-globulin fraction [%]. This is a method for classifying and evaluating the risk of tumor and cancer by performing multivariate analysis.

In the data collection method used for classification in Example 2, serum is applied to a support immersed in a buffer solution, the support is electrophoresed at a predetermined liquid temperature and fractionated, and proteins in the serum are collected. ALP isozyme staining solution is used to detect ALP isozyme, and the protein image and ALP isozyme are combined to determine the mobility, chromosome shape, shading, etc. of each isozyme To detect the movement of cancer and evaluate the risk of tumor and cancer.

The data collection method used when classifying in Example 2 shows the change state of the decrease in albumin fraction and the increase in α1-globulin fraction, α2-globulin fraction, and γ-globulin fraction, which appear in the protein image. By identifying, tumor risk and cancer risk assessment are classified into several stages.

<Explanation of albumin fraction>
The data collection method used in classifying clinical cancer stage of Example 2, albumin, alpha 1-globulin fraction (many immunosuppressants) used. In particular, the α1-globulin fraction functions as a good parameter. Note that the change in the protein image is a phenomenon that occurs also in an inflammatory disease, so it is necessary to avoid the case caused by the inflammatory disease. Therefore, more accurate cancer classification becomes possible by measuring the C reactive protein value (C inflammatory protein value, CRP value) and the sialic acid value together.

  For example, cirrhosis and chronic hepatitis tend to decrease albumin and increase γ-globulin. Albumin is a substance that is produced in the liver, is used to regulate blood osmotic pressure, and is used to carry hormones and harmful substances. Albumin has the property of decreasing when there are many diseases.

<Description of globulin fraction>
(1) α1-globulin fraction The α1-globulin fraction increases this fraction in the acute phase of inflammation, cancer, stress and rheumatic diseases. Antitrypsin, glycoprotein soluble in α1, prothrombin, chymotrypsin, elastase and protease are included in this fraction. The two enzymes here are impeded by lung tissue, which is produced from polymorphonuclear cells that granulocytes can destroy, so that the leading role of α1 antitrypsin in humans is the protection of lung tissue appear. The AFP is included in this fraction.

(2) α2-globulin fraction The α2-globulin fraction includes α2-HS globulin fraction, ceruloplasmin, erythropoetin, cholinesterase, contact globulin, and α2-macroglobulin. aptoglobulin binds to hemoglobin and is circulated into the blood circulation, increasing nonspecific stress responses. Chronic protein loss α2-macroglobulin increases. Ceruloplasmin is produced in the liver by adding iron to the oxidative enzyme and facilitating iron transport with transferrin.
α2-HS glycoprotein is considered to be a non-specific opsonin.

(3) β-globulin fraction The β-globulin fraction includes transferrin, β lipoprotein, complements and hemopexin. Transferrin is produced in the liver and correlates with iron transport, and 60% of this fraction is attributed to this mechanism. Lipids act as an integral part of cell membrane progenitors, with steroids and bile acids, the largest fragment being β-lipoprotein.
Hemopexin is used in hemoglobin molecules that make heme in the iron nucleus. Complements is a complex system of serum proteins against infection.

(4) γ-globulin fraction The γ-globulin fraction includes IgA, IgG, and IgM. In the fraction of IgA, antitoxins, antimicrobial agglutinins, cold agglutin and isoagglutin are included. This correlates with salivery.

  IgG includes bacterial, viral and toxin antibodies. This fraction increases because of acute and chronic diseases. IgM increases with many diseases.

FIG. 10 is a graph showing the protein fraction names, the results, the unit, and the reference value, and checking the mutation points of each protein fraction and representing the area ratio of each. FIG. 11 is an analysis diagram of each protein fraction.
The protein fraction, and as a result, the unit and the reference value, as shown in Table 1 and the fraction No. 1 indicates albumin fraction (Alb), the protein fraction result is 58.7, and the reference value is 55.8-66.1.
Fraction No. 2 shows an α1-globulin fraction (α1-G), a protein fractionation result of 3.1, and a reference value of 2.9 to 4.9.
Fraction No. 3 shows an α2-globulin fraction (α2-G), a protein fractionation result of 8.7, and a reference value of 7.1 to 11.8.
Fraction No. 4 shows a β1-globulin fraction (β1-G), a protein fraction result of 6.1, and a reference value of 7.7 to 7.2.
Fraction No. 5 shows a β2-globulin fraction (β2-G), a protein fractionation result of 3.7, and a reference value of 3.2 to 6.5.
Fraction No. 6 shows a γ-globulin fraction (γ-G), a protein fraction result of 19.7, and a reference value of 11.1-18.8.

<Method to classify into 4 periods>
Table 1, Fig. 11, based on the results of FIG. 12, the data acquisition method used in classifying clinical cancer stage of Example 2, for cancer clinical cancer stage became 1 gram or more for the life of cancer 4 Classify by period. For example, the risk of cancer in the clinical cancer stage is classified as follows.
In the first period, when the albumin fraction is 65% or more, the α1-globulin fraction is less than 2.5%, and the γ-globulin fraction is less than 16%,
In the second period, when the albumin fraction is 60% to less than 65%, the α1-globulin fraction is 2.5% to less than 3.0%, and the γ-globulin fraction is less than 16% to less than 20%,
In the third stage, when the albumin fraction is 55% to less than 60%, the α1-globulin fraction is 3.0% to less than 4.0%, and the γ-globulin fraction is 20% to less than 23%,
In the fourth stage, when the albumin fraction is less than 55%, the α1-globulin fraction is 4.0% or more, and the γ-globulin fraction is 23% or more, the risk of cancer is classified into four stages.
In addition, these numerical values are illustrations, Comprising: It is not limited to this numerical value.

Thus, in the data acquisition process used in classifying clinical cancer stage of Example 2, by adding biochemical biopsy protein fraction, cancer, clinical cancer, from equal to or more than 1 gram Accurately classify cancer stages. If the cancer is classified according to the classification method of the present invention, the prevention of cancer, the prevention of recurrence, the therapeutic effect of anticancer agents, and the progression of cancer can be analyzed almost accurately and numerically. Whether health foods are effective for the person, whether they have a diet, whether cancer treatment is appropriate, and if TMCA screening is performed before and after surgery for cancer, it may be early cancer even without laparotomy. It can be clearly determined whether the cancer is advanced. Of course, if an operation is performed and a TMCA examination is performed after the operation, it can be reliably determined whether the cancer has been left uncut or whether the operation was successful.

The TMCA method (tumor marker combination assay) is a method for comprehensively determining in vivo (internal environment) toxins. This method classifies the risk level comprehensively by determining the toxin (tumor marker) produced by the cancer, and can use it as a health level classification. This screening has attracted attention because it is the only test method that can predict cancer. This TMCA method is a method of accurately classifying the risk of cancer into five stages from “clinical cancer” to “ideal health” with only 20 cc blood collection and simple oriental medical examination.

  The health level classification of the internal environment of a living body can determine the health status of each person at an unaffected stage. This is an extremely effective method that can objectively determine whether the lifestyle habits of each person, such as exercise and health foods, are more healthy or unhealthy.

Data collection method used in classifying clinical cancer stage of Example 2 corresponds to health barometer, together many misdiagnosis reliably prevented that was determined just like poor image diagnosis.

  Since the change in the protein image is a phenomenon that occurs also in an inflammatory disease, it is necessary to avoid the participation rate due to the inflammatory disease. Therefore, more accurate cancer classification becomes possible by measuring the C reactive protein value (C inflammatory protein value, CRP value) and the sialic acid value together.

  Measurement with high measured value of sialic acid value by subtracting the involved part from α1-globulin fraction according to the measured value of C reactive protein value (C inflammatory protein value, CRP value) By determining by subtracting from the α1-globulin fraction according to the value, it is possible to classify the risk of cancer by excluding the inflammatory part at the time of evaluation.

Data collection method used in classifying clinical cancer stage of the present invention can be carried out in conventional cancer classification. Although the criteria are slightly different for sarcomas and the like, it is also possible to apply the clinical cancer stage classification method of the present invention.

<Test>
Next, test examples based on the data collection method used for classifying the clinical cancer stage of the present invention will be described.
The data collection method used when classifying the life of the cancer of the present invention has made several attempts to improve the ability of differential diagnosis of early cancer and benign using tumor markers. Among them, serum protein fractions (immuno-regulatory α-globulin and tissue polypeptide antigen (tissue po1ypeptide antigen (TPA)) are combined, and the product value of α1-globulin × α2-globulin and the product value of TPA × α1-globulin The clinical usefulness as a tumor marker was evaluated.The α1-globulin and α2-globulin fractions reflect the growth of cancer, and are useful for screening for cancer by introducing multivariate analysis. It is known as a tumor-specific and growth-related tumor marker (reflecting the proliferation ability of cells) contained in the blood and leaked into the blood.

<Target and method>
The subjects were (1) 120 serum samples (early colorectal cancer 40, benign colorectal disease 30, healthy 50, age 63.2 ± 12.8 mean ± standard deviation (mean ± SD), 61.8 ± 14.1, 60.8 ± 12.1, equal number of men and women)
(2) 237 cancer patients (breast cancer 58, stomach cancer 38, colorectal cancer 29, lung cancer 20, uterine cancer 18, ovarian cancer 15, pharyngeal pharyngeal cancer 7, spleen cancer 5, liver cancer 4, tongue cancer 1, and others 29), There were 100 benign diseases and 50 healthy individuals (ages 22-81, 46.4 ± 13.5, male / female ratio 2: 3).

  The α1-globulin fraction and the α2-globulin fraction were measured by the serum protein fractionation method by cellulose acetate electrophoresis, and the serum TPA was measured by the RIA two-antibody method. α1-globulin fraction, α2-globulin fraction, TPA were measured simultaneously, α1 × α2 product value and TPA × α1 product value were calculated, and product value distribution, positive rate, mean ± SD in each case were obtained. . Furthermore, in the subject (2), cancer cases were classified according to clinical progression (stage I-IV), and the positive rate and mean ± standard deviation (mean ± SD) in each stage were compared.

<Measurement results>
Figure 12 is a data acquisition method used in classifying clinical cancer stage of Example 2, a distribution diagram showing the distribution of serum α1- globulin × alpha2-globulin product value in early colon cancer when classified, The upper row shows early colorectal cancer (40 cases), the middle row shows benign tumors (30 cases), and the lower row shows healthy individuals (50 cases). FIG. 13 is a distribution diagram showing a distribution state of product values of serum TPA × α1-globulin in early colorectal cancer when classified by the clinical cancer stage classification method of Example 2, and the upper stage is an initial colorectal cancer (40 Example), the middle row shows benign tumors (30 cases), and the lower row shows healthy subjects (50 cases).
The distribution of the product value of α1-globulin × α2-globulin and the product value of TPA × α1-globulin in early colon cancer was examined. Here, mean + SD of a healthy person example is 30.0 for α1 × α2 and 41 l. For TPA × α1. The cut off value was set to 30 and 500, respectively. The mean ± SD and positive rate for each disease of α1-globulin × α2-globulin is early colorectal cancer: 34.8 (± 16.7), (48%),
Benign colon disease: 27.5 (± 9.8), (20%),
Healthy subjects: 20.9 (± 4.5), 2%), and significant differences were observed between the three individuals.

For TPA × α1-globulin, early colorectal cancer: 527.8 (± 353.6), (53%),
Benign colon disease: 393.3 (± 195), (23%),
Healthy: 25 l. 5 (± 80.2) and (2%), and a significant difference was observed between the three.

  Next, α1-globulin × α2-globulin and TPA × α1-globulin were combined in a combination assay. As shown in Table 2, 68% showed positive in any one of them, and the positive rate was higher than that in each case alone. Both positive cases and negative cases were 32.5% (13/40), and both showed a tendency to increase. The specificity of the healthy group was as high as 96%, but it was slightly reduced to 67% in the benign group.

<Results of various cancer cases>
FIG. 14 is a distribution diagram in which the product value of α1-globulin × α2-globulin in various cancer cases was examined. FIG. 15 is a distribution diagram showing the product value of TPA × α1-globulin in various cancer cases.
The specimens were examined for distribution of product values of α1-globulin × α2-globulin and TPA × α1-globulin in various cancer cases. In both cases, the positive rate increased as the cancer progressed, regardless of the location of the cancer. By the way, the relationship between cancer progression, mean ± SD, and positive rate (Table 3) was observed.
For α1-globulin × α2-globulin, Phase I: 17.3 (± 6.1),
Stage II: 22.5 (± 10.2)
Stage III: 28.8 (± 12.6),
Stage IV: 44.3 (± 32.9)
The positive rate increased to 6, 17, 38.79% respectively. The mean ± SD of benign diseases and healthy subjects were 17.9 ± 4.6 and 17.7 ± 3.0, respectively, and the false positive rates were 1 and 0%, but no significant difference was observed between them, but the cancer group A significant difference was observed with respect to (except for stage I).

For TPA x α1-globulin,
Stage I: 308.5 (± 403.2),
Stage II: 356.6 (± 236.5),
Stage III: 723.5 (± 1012.4),
Stage IV: 3132.2 (± 5624.2)
The positive rate increased to 6, 14, 44.76%, respectively. The mean ± SD of benign and healthy were 223.6 ± 90.0 and 205.9 (± 40.7), respectively, and the pseudo-positive rates were 1 and 0%, and there was no significant difference between them, A significant difference was observed between the cancer groups.

Next, when α1-globulin × α2-globulin and TPA × α1-globulin were subjected to a combination assay, one that showed positive results in the progression of cancer.
I (period): 11 (%),
II (term): 26,
III (phase): 58,
IV (period): It increased to 88, and the positive rate further increased in each stage as compared with the case of each individual. It was 2 and 0% in benign and healthy, and a significant difference was observed between the cancer group including early cancer.
The mean 12SD in the healthy group of this facility was α1 × α2: 23.8 and TPA × α1: 287.3.

  The product value of α1-globulin × α2-globulin and the product value of TPA × α1-globulin increased with the progression of cancer in both the mean value and the positive rate in various cancer cases, suggesting its usefulness as a tumor marker. In particular, both combination assays have a higher positive rate and are useful for differential diagnosis of early cancer and benign, and are expected to be applied to screening.

<Determination of discriminant function>
1. Determination of Discriminant Function Next, using the data collection method used when classifying cancer according to Example 2 of the present invention, 100 cases morphologically diagnosed with cancer and 100 cases not diagnosed with cancer Randomly extracted and tested as a patient group and a healthy group, respectively. This is designated as sample A.
Analysis I: The sample A data was analyzed as it was.
Analysis II: Patient group excluding liver disease / boundary zone values and particularly abnormal values from the data of specimen A. 50 cases were selected for each healthy group and analyzed.
Analysis III: Data obtained by converting each measurement value in the sample A into a distance (distance from the cut off value) from the normal range (Alb ≧ 58.0, al ≦ 3.0, α2 ≦ 9.0) (Alb) ′-(al) ′. (Α2) ′), taking Alb as an example, all values greater than 58.0 are 0.57 for 1.0 and 56.0 for Respectively converted to 2.0.
For the analysis, a discriminant function was determined by using a program that obtains each coefficient of the discriminant, each value distribution, correlation, etc. by inputting data using a computer.

<Test of obtained discriminant function>
Separately from the above sample A, 100 cases of each of the patient group and the healthy group were randomly extracted as sample B. Each discriminant function was tested.

<Clinical application of the obtained discriminant function>
Furthermore, cancer diagnosis was performed on specimens provided by others (excluding 15 healthy subjects, 20 early lung cancers, 20 early colon cancers, and benign tumors) using the discriminant function obtained by the determination of the discriminant function.

<Calculation formula>
As the calculation formula used for the data collection method used when classifying the cancer of Example 2, the formula shown in the following formula 1 was considered useful.
In this formula 1, when Z ≧ 0, a healthy person (normal) is determined, and when Z <0, cancer is determined.

  The prevalence rate for detecting cancer as cancer (sensibitinity: hereinafter abbreviated as ser), the disease-free accuracy rate for determining healthy as healthy (specificity: hereinafter abbreviated as spe), and the sum of both, In the sample A when determining the mathematical formula, Sen was 64%, spe was 91%, and the correct diagnosis rate was 77.5%. In the test for specimen B, Sen was 75%, spe was 92%, and the correct diagnosis rate was 83.5%. In another sample, Sen was 97.6%, spe 26.7%, and the correct diagnosis rate was 78%.

In the data collection method used when classifying the cancer of Example 2, a good accuracy rate was obtained by using multivariate analysis of serum protein fractions. This is thought to be due to the fact that abnormalities appear in each individual fraction as the cancer grows, making it possible to comprehensively judge them.
2) In the conventional literature, there is a report that there was 55.2% discrimination ability when albumin and α2-globulin were used and lung cancer was discriminated against a human dock subject. When α1-globulin was added to this, the correct diagnosis rate was further increased. In the classification method of Example 2, albumin, α1-globulin, and α2-globulin were used. However, the β-globulin fraction has little effect on discrimination of cancer and has other similar effects.

<Biochemical biopsy of protein fraction>
Biochemical biopsy was performed on the protein fraction. That is, the protein fraction was analyzed by diagnosing a disease by collecting a part of a living tissue or organ. This biochemical biopsy can be performed on patients suspected of having a malignant cancer and is the same as that pathologically diagnosed using tissues such as the skin, stomach, intestine, liver, lungs, and kidneys. is there.
The protein fraction is electrophoresed into five basic bands. Among them, albumin, α1-globulin fraction, and α2-globulin fraction are closely related to cancer growth. The first band is albumin. Produced characteristically in the liver, it regulates the osmotic pressure of blood and helps transport substances and preserve proteins. Albumin decreases in liver disease, kidney disease, and systemic disease.

  The second band is the α1-globulin fraction. In this, there is 70-90% α1-antitrypsin. α1-acid glycoprotein, α1-lipoprotein, prothrombin, transcoatn, teloxin-binding globulin are included.

An increase in the α1 fraction occurs as an acute reaction of inflammation, cancer, stress, hemorrhagic abnormalities.
α1-acid glycoprotein decreases with hepatitis, kidney damage, and cachexia.
α1-antitrypsin is a typical protease inhibitor for proteolytic enzymes. α1 fetal protein occurs in this band.

The α2-globulin fraction contains haptoglobulin, α2-macroglobulin, α2-HS glycoprotein, ceruloplasmin, erythropoietin, and cholinesterase.
Haptoglobulin acts to bind hemoglobin.
Haptoglobulin increases in the early stages of cancer. α2-macroglobulin appears in the forward tilt of the α2 band. α2HS globulin glycoprotein may be non-specific opsonin.

In addition, the present invention examines whether there is a microcancer somewhere in the body, analyzes the ALP isozyme pattern, analyzes the tumor marker, and analyzes the serum protein fraction, and comprehensively evaluates, Not only to detect early cancers in specific organs, but also to identify high-risk groups of micro-cancers at any site and early cancers in clinical cancer stages, and classify advanced cancer stages to prevent and treat cancer As long as the contribution can be made and the treatment progress can be correctly evaluated and scientific countermeasures can be proposed, the present invention is not limited to the embodiment of the invention described above, and various changes can be made without departing from the scope of the invention. It is.
In addition, the present invention is limited to the above-described embodiments as long as it can detect both micro cancers in the preclinical cancer stage and the stage of the clinical cancer stage in the life of the cancer and accurately determine and classify the risk level. However, various modifications can be made without departing from the scope of the present invention.

The present invention can detect any of the data used for the detection of pre-clinical cancer stage micro cancer and clinical cancer stage early cancer in the lifetime of cancer, and can be used to accurately determine and classify the risk. it can. The present invention can be used as a barometer for measuring the lifetime of cancer. In other words, it can be used as a barometer of true health by taking the life of cancer, which was the greatest enemy of humanity, in reverse.

Claims (6)

Classify the life of a cancer in order to discover the movements of minute cancers that occur in the human body and to analyze the data in two stages of preclinical cancer stage and clinical cancer stage. A data collection method used when
About data used for preclinical cancer stage analysis,
In the ALP I to ALP IV pattern of the ALP isozyme, data on the appearance and ratio of ALP I, activity values of ALP II and ALP III were collected, examination of the numerical data ratio, and steepness of ALP II and ALP III Analyzing data on the proliferation activity of cancer cells from APA determined from the ALP isozyme angle indicating
Furthermore, in order to avoid the cause of inflammatory diseases, it also occurs in inflammatory diseases from numerical data obtained by combining C reactive protein values (C inflammatory protein values, CRP values) and sialic acid values. by analyzing by subtracting the numerical data of the involved parts, and data analysis for the presence of micro-cancer and its growth conditions occurring,
About data used for analysis of clinical cancer stage,
A decrease in albumin fraction appearing in the protein image,
Collect data of change states of α1-globulin fraction, α2-globulin fraction and γ-globulin fraction increase, and analyze each data
Furthermore, in order to avoid the cause of inflammatory diseases, the data of the C reactive protein value (C inflammatory protein value, CRP value) and the sialic acid value data are combined in the data analysis of the protein image. In order to analyze the risk of cancer and the risk assessment of cancer in several stages by subtracting the numerical data of the involved part that also occurs in inflammatory diseases from the measured numerical data and analyzing it,
Serum is applied to a support immersed in a buffer solution, the support is electrophoresed at a predetermined liquid temperature, fractionated, proteins in the serum are separated, and developed with an ALP isozyme staining solution. Data used to classify the life of a cancer, characterized by detecting ALP isozymes, combining the protein image and ALP isozymes, and collecting each data on mobility, chromosome shape, and shade of each isozyme Collection method. Classify the life of a cancer in order to discover the movements of minute cancers that occur in the human body and to analyze the data in two stages of preclinical cancer stage and clinical cancer stage. A data collection method used when
About data used for preclinical cancer stage analysis,
In the ALP I to ALP IV pattern of the ALP isozyme, data on the appearance and ratio of ALP I, activity values of ALP II and ALP III were collected, examination of the numerical data ratio, and steepness of ALP II and ALP III Analyzing data on the proliferation activity of cancer cells from APA determined from the ALP isozyme angle indicating
Furthermore, in order to avoid the cause of inflammatory diseases, it also occurs in inflammatory diseases from numerical data obtained by combining C reactive protein values (C inflammatory protein values, CRP values) and sialic acid values. by analyzing by subtracting the numerical data of the involved parts, and data analysis for the presence of micro-cancer and its growth conditions occurring,
About data used for analysis of clinical cancer stage,
About cancer that became more than 1 gram in clinical cancer stage,
In the first period, when the albumin fraction is 65% or more, the α1-globulin fraction is less than 2.5%, and the γ-globulin fraction is less than 16%,
In the second period, when the albumin fraction is 60% to less than 65%, the α1-globulin fraction is 2.5% to less than 3.0%, and the γ-globulin fraction is less than 16% to less than 20%,
In the third stage, when the albumin fraction is 55% to less than 60%, the α1-globulin fraction is 3.0% to less than 4.0%, and the γ-globulin fraction is 20% to less than 23%,
In the 4th period, when the albumin fraction is less than 55%, the α1-globulin fraction is 4.0% or more, and the γ-globulin fraction is 23% or more, the data is such that the risk of cancer becomes 4 stages. As well as analyzing
In order to avoid the cause of inflammatory diseases, each numerical value obtained by measuring C reactive protein value (C inflammatory protein value, CRP value) and sialic acid value at the time of data analysis of the protein image In order to analyze the risk of cancer and the risk assessment of cancer in several stages by subtracting the numerical data of the part involved in inflammatory diseases from the data and analyzing it ,
Serum is applied to a support immersed in a buffer solution, the support is electrophoresed at a predetermined liquid temperature, fractionated, proteins in the serum are separated, and developed with an ALP isozyme staining solution. Data used to classify the life of a cancer, characterized by detecting ALP isozymes, combining the protein image and ALP isozymes, and collecting each data on mobility, chromosome shape, and shade of each isozyme Collection method. For use in the analysis of preclinical cancer stage, regarding the APA data obtained from the ALP isozyme,
The angle of the line connecting the anode side tangent of ALP II and the peaks of ALP II and ALP III is θ ₁ °,
From this two tangent intersection, the distance to the peak of the ALP III as Omega1cm, shown in APA = ω1 / θ _1, when the ALP IV have appeared, the intersection and ALP III - IV of the tangent of the ALP II a length of up to a peak as Omega2cm, data acquisition method used when be expressed in APA = ω2 / θ _2, to classify claim 1 or lifetime of 2 cancers characterized. Regarding the data used for the analysis of preclinical cancer stage, the serum was heat-treated at 56 ° C. for 10 minutes to analyze the reconstructed pattern data of each ALP isozyme pattern from ALP I to ALP IV. ALP II, ALP III and A method for collecting data used in classifying the life of a cancer according to claim 1, 2 or 3 , wherein ALP IV is accurately identified. For the data used in the analysis of preclinical cancer stage, the proliferation activity of cancer cells from the change in the pattern of the ALP isozymes as well as data analysis,
Tumor growth level by tumor marker, stage I, ideal state without micro cancer, stage II, pre-cancer state at microgram level, stage III, pre-cancer state at milligram level, stage IV, pre-clinical cancer state, and then data analysis the state of 1g or more cancer is estimated to be present with the tumor growth of stage 5 stage of the stage V,
The data collection method used for classifying the life of a cancer according to claim 4 , wherein the data analysis of the presence and growth state of the microcancer is performed by using the data analysis of the change with time of the tumor marker. . For data to be used for analysis of clinical cancer stage, the C reactive protein value (C inflammatory protein levels, CRP values) and the measured value of, from the numerical data of the measurement values of the sialic acid level, even in inflammatory diseases 3. The data collection method for use in classifying the life of a cancer according to claim 1 or 2 , wherein the analysis is performed by subtracting the α1-globulin fraction of the part involved .